Defect detection of backlight panel surfaces using
نویسندگان
چکیده
In this study, a filter-design scheme based on Independent Component Analysis (ICA) is proposed for defect inspection in backlight panels. In a backlight panel image, the gray levels of defects and the background are very similar and result in a low-contrast image which makes the defect detection task difficult. The proposed method is based on an ICA filtering scheme that computes the output response of energy from the convolution of an inspection image with the ICA filter. The ICA model with prior constraints is applied to determine the filter so that the convolved responses of an inspection image have the variance as small as possible. In this study, Particle Swarm Optimization (PSO) algorithm is used to solve for the constrained ICA model. Experimental results have shown that the proposed method can effectively detect defects in low-contrast backlight panel images.
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